Packaging box UV printing method and device and computer equipment

Abstract

The invention relates to the technical field of UV printing, and discloses a packaging box UV printing method and device and computer device.The method comprises the steps that feature extraction is conducted on CAD model data of a packaging box, and a feature data set of the packaging box is obtained; carrying out coordinate mapping on the working space of the robot to obtain a conversion matrix and space calibration data of the mounting position of the UV nozzle; edge detection and feature point matching are conducted, and position coordinate data and posture angle data of the UV printing area are obtained; performing multi-section track planning on the ink jet track to obtain initial jet printing track control data; and performing synchronous control calculation on the UV light source to obtain a UV light source power modulation parameter and UV light source trigger time sequence data. According to the method, by dynamically adjusting the power output and the triggering time sequence of the UV light source, uniform curing of the ink droplets is achieved, the problem that curing of the ink droplets at different positions is not uniform is effectively solved, and the printing quality is improved.

Description

Technical Field

[0001] The present invention relates to the field of UV printing technology, and in particular to a packaging box UV printing method, device and computer equipment. Background Art

[0002] In the field of packaging printing, UV printing technology is widely used due to its advantages such as environmental protection, quick drying, and high gloss. Traditional UV printing equipment mainly uses fixed UV light sources and a single printing track mode, which has poor adaptability when processing packaging boxes of different shapes and materials. Especially in the UV printing process of complex curved surfaces and special material packaging boxes, due to the lack of precise spatial position control and real-time UV energy adjustment mechanism, quality problems such as uneven ink drop curing and printing accuracy deviation are prone to occur.

[0003] As the packaging industry's demand for personalized and refined printing continues to increase, existing UV printing equipment faces many challenges in processing high-precision and diversified packaging boxes. On the one hand, traditional UV printing systems lack the ability to accurately identify and dynamically track the surface features of packaging boxes, making it difficult to ensure the precise positioning of ink droplets during the printing process; on the other hand, the energy output of UV light sources often uses a fixed parameter mode, which cannot be adjusted in real time according to the curing requirements of ink droplets at different locations, affecting the consistency of printing quality. Summary of the invention

[0004] The present invention provides a packaging box UV printing method, device and computer equipment. The present invention realizes uniform curing of ink droplets by dynamically adjusting the power output and triggering timing of the UV light source, effectively solves the problem of uneven curing of ink droplets at different positions, and improves the printing quality.

[0005] In a first aspect, the present invention provides a packaging box UV printing method, the packaging box UV printing method comprising: Perform feature extraction on the CAD model data of the packaging box to obtain a feature data set of the packaging box; Carry out coordinate mapping of the robot workspace to obtain the conversion matrix between the visual coordinate system and the robot base coordinate system and the spatial calibration data of the UV nozzle installation position; Based on the conversion matrix and the spatial calibration data, edge detection and feature point matching are performed on the packaging box to obtain position coordinate data of the packaging box and posture angle data of the UV printing area; According to the position coordinate data and the attitude angle data, a multi-segment trajectory planning is performed on the inkjet trajectory to obtain initial printing trajectory control data that meets the UV ink droplet jetting spacing requirement; Based on the initial printing trajectory control data, a UV light source synchronous control calculation is performed to obtain UV light source power modulation parameters and UV light source triggering timing data.

[0006] In a second aspect, the present invention provides a packaging box UV printing device, the packaging box UV printing device comprising: A feature extraction module is used to extract features from the CAD model data of the packaging box to obtain a feature data set of the packaging box; The coordinate mapping module is used to coordinate map the robot workspace, obtain the conversion matrix between the visual coordinate system and the robot base coordinate system, and the spatial calibration data of the UV nozzle installation position; A feature point matching module, used to perform edge detection and feature point matching on the packaging box based on the conversion matrix and the spatial calibration data, to obtain position coordinate data of the packaging box and posture angle data of the UV printing area; A trajectory planning module, used to perform multi-segment trajectory planning on the inkjet trajectory according to the position coordinate data and the attitude angle data, and obtain initial printing trajectory control data that meets the UV ink droplet jetting spacing requirement; The synchronous control module is used to perform UV light source synchronous control calculation based on the initial printing trajectory control data to obtain UV light source power modulation parameters and UV light source triggering timing data.

[0007] The third aspect of the present invention provides a packaging box UV printing device, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory so that the packaging box UV printing device executes the above-mentioned packaging box UV printing method.

[0008] In the technical solution provided by the present invention, by performing feature extraction and edge detection on the CAD model data of the packaging box, the precise positioning and posture recognition of the packaging box are realized in combination with machine vision technology, and the positioning deviation in the printing process is effectively avoided. A multi-segment trajectory planning method is adopted, and the uniformity of the ink drop spacing and the consistency of the curing effect are ensured through dynamic optimization of the inkjet trajectory and synchronous control of the UV light source. An accurate conversion relationship between the visual coordinate system and the robot base coordinate system is established, and the high-precision calibration of the UV nozzle position is realized, thereby improving the spatial positioning accuracy of the printing system. By calculating the overlap rate and energy density distribution of the UV curing area in real time, the power output and trigger timing of the UV light source are dynamically adjusted to achieve uniform curing of the ink droplets. Based on the synchronous optimization of the spot coverage range parameters and the ink drop deposition time data, the precise coordination of the UV light source and the inkjet system is achieved, and the stability of the printing quality is guaranteed. By real-time compensation of the UV light source power and optimized calculation of energy distribution, the problem of uneven curing of ink droplets at different positions is effectively solved, and the printing quality is improved.

[0009] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0010] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 A schematic diagram of an embodiment of a UV printing method for a packaging box in an embodiment of the present invention; Figure 2 This is a schematic diagram of an embodiment of a packaging box UV printing device in an embodiment of the present invention; Figure 3 It is a schematic diagram of an embodiment of a packaging box UV printing device in an embodiment of the present invention. DETAILED DESCRIPTION

[0012] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0013] The terms "including" and "having" and any variations thereof mentioned in the embodiments of the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device end including a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or device ends.

[0014] To facilitate understanding of this embodiment, a packaging box UV printing method disclosed in an embodiment of the present invention is first described in detail. Figure 1 As shown, the method comprises the following steps: 101. Perform feature extraction on the CAD model data of the packaging box to obtain a feature data set of the packaging box; It is understandable that the execution subject of the present invention may be a packaging box UV printing device, or a terminal or a server, which is not limited here. The embodiment of the present invention is described by taking a server as the execution subject as an example.

[0015] Specifically, a geometric edge extraction operation is performed on the CAD model of the packaging box, and a high-precision edge detection algorithm is used, such as a gradient-based Canny algorithm or an adaptive edge detection method based on curvature changes, to ensure that the extracted edge contour data can accurately reflect the actual geometric shape of the packaging box. After completing the edge detection, the detected edge information is converted into a set of edge segments through vectorization processing to form a structured data format. The edge segment set is subjected to intersection calculation to identify key corner points in the packaging box structure. The intersection calculation determines the intersection coordinates by solving the equation group of the intersecting segments, and the intersections are screened in combination with the geometric characteristics of the packaging box to ensure that the retained corner points meet the structural characteristics of the actual packaging box. For example, some invalid intersections caused by CAD errors or edge detection noise should be eliminated, while real corner points with strong geometric constraints should be retained first. After completing the corner point screening, the connection relationship between the corner points is analyzed to construct a complete corner point topological structure. Curvature analysis and surface smoothness calculation are performed on the edge contour data to obtain material information on the surface of the packaging box. The core of curvature analysis is to calculate the local and global curvature distribution of edge curves, which is achieved through differential geometry methods. For example, the curvature calculation formula is used to quantify the curvature characteristics of different areas of the packaging box, so as to determine which areas are flat, which areas are curved, and which areas have large curvature changes. The surface smoothness calculation adopts a method based on normal vector deviation, that is, the surface uniformity is measured by calculating the local normal vector change rate to obtain the material uniformity data of the packaging box surface. Based on the corner point position data and material uniformity data, the resolution of UV printing is optimized. The inkjet resolution parameters are adjusted according to the material uniformity data. For example, a higher inkjet resolution is used for areas with higher material uniformity, while the resolution is reduced for areas with lower material uniformity to reduce the printing blur caused by ink diffusion. The inkjet resolution also needs to be optimized in combination with the geometric characteristics of the packaging box. For example, the inkjet density is appropriately increased in areas with larger edge curvature to ensure the clarity of the printed details. At the same time, since UV inkjet technology relies on UV light source for curing, and the reflection characteristics of UV light on different material surfaces will affect the curing effect, the reflection coefficient is spatially distributed and mapped to construct a reflection intensity distribution map of the UV printing area. The calculation of the reflection coefficient is based on the refractive index and surface roughness of the material surface, and combined with the illumination modeling method to simulate the reflection of the UV light source in different areas to obtain the reflection intensity distribution map. Based on the reflection intensity distribution map, the light intensity compensation coefficient of the UV light source is calculated, that is, the power of the UV light source is appropriately reduced in the area with strong reflection, and the power of the light source is increased in the area with weak reflection to ensure that the UV ink can be cured evenly and improve the printing quality. A complete feature data set is constructed based on edge profile data, corner position data, inkjet resolution parameters and reflection coefficient.

[0016] 102. Coordinate mapping is performed on the robot workspace to obtain the conversion matrix between the visual coordinate system and the robot base coordinate system and the spatial calibration data of the UV nozzle installation position; Specifically, the calibration plate is photographed by a camera, and the feature point information on the calibration plate is extracted by an image processing method. The calibration plate adopts a regular chessboard or dot array, and its corner points or feature points are extracted by a sub-pixel precision detection algorithm. Harris corner detection, SIFT or the sub-pixel corner detection method provided by OpenCV are used to obtain high-precision pixel coordinate data, and the feature point coordinates are optimized by combining the sub-pixel interpolation algorithm so that the obtained corner point data can meet the accuracy requirements. The pixel coordinate data and sub-pixel coordinate data are calibrated and calculated by internal parameters. The internal parameters of the camera include focal length, principal point coordinates, pixel scaling factor and distortion coefficient. The calculation of these parameters is solved by Zhang Zhengyou calibration method or least squares calibration method based on optimization iteration. The projection model of the camera is constructed by using calibration plate images taken at multiple different angles and positions, and the camera's internal parameter matrix, i.e., focal length and principal point coordinates, is solved by the least squares optimization algorithm. At the same time, since the industrial camera lens has radial distortion and tangential distortion, the distortion coefficient matrix is ​​calculated, and the five-parameter model (k1, k2, p1, p2, k3) is used for distortion correction to eliminate the bending distortion of the straight line in the image. The camera's extrinsic calibration is performed based on the intrinsic parameter matrix and the distortion coefficient matrix to solve the camera's posture information in the world coordinate system. The core of the extrinsic calibration is to calculate the rotation matrix and translation vector of the camera and establish a projection transformation matrix from the camera coordinate system to the world coordinate system. Based on the PnP algorithm, the three-dimensional physical coordinates of the corner points of the calibration plate are matched with their corresponding image pixel coordinates, and the camera extrinsic parameters are optimized by minimizing the projection error. In order to improve the calibration accuracy, nonlinear optimization methods such as the Levenberg-Marquardt algorithm are used to optimize the spatial pose of the camera extrinsic parameters to obtain the projection transformation matrix. Based on the projection transformation matrix, the coordinates of the robot's end reference point are transformed from the visual coordinate system to the robot base coordinate system. A reference calibration tool of known size, such as a cylindrical pin or a reference block with precise markings, is installed at the end of the robot, and its pixel coordinate data is obtained by camera shooting. Using the projection transformation matrix, these pixel coordinates are converted into three-dimensional spatial coordinates, and the transformation matrix between the visual coordinate system and the robot base coordinate system is calculated through the coordinate alignment algorithm, where the matrix contains the rotation matrix and the displacement vector, so as to achieve accurate mapping from the visual measurement coordinates to the robot base coordinates. The position of the UV nozzle is calibrated to calculate its offset relative to the flange at the end of the robot. The multi-point sampling measurement method is adopted, that is, the injection center of the UV nozzle is measured at different positions of the robot end, and the installation offset vector of the UV nozzle relative to the robot end is calculated based on the spatial distribution of these measurement points. The coordinate system compensation calculation is performed according to the transformation matrix and the installation offset vector to obtain the spatial calibration data of the UV nozzle installation position.

[0017] 103. Based on the conversion matrix and the spatial calibration data, edge detection and feature point matching are performed on the packaging box to obtain position coordinate data of the packaging box and posture angle data of the UV printing area; Specifically, a multi-scale edge detection operation is performed on the real-time image data of the packaging box. Since the surface material, lighting conditions and camera viewing angle of the packaging box may cause noise or weak edges in the edge detection process, the multi-scale edge detection method can extract edge information at different resolutions and filter scales to enhance the robustness of edge detection. In this process, the Canny edge detection combined with the Gaussian pyramid filter method is used to extract edge points from coarse to fine level, and a complete edge point set is constructed. At the same time, in order to improve the reliability of edge information, the edge intensity matrix is ​​calculated so that weak edges and pseudo edges can be optimized and screened in the subsequent processing process. The edge point set is adaptively segmented to dynamically adjust the threshold of edge detection to ensure that key edges can still be accurately extracted in complex lighting environments. Morphological processing methods are used to optimize edge data, including expansion, corrosion, closing operations, etc., to remove isolated points and fill broken edges, and obtain the refined edge contour and contour segment data of the packaging box. Based on the refined edge contour, feature point extraction and descriptor calculation are performed to obtain the key feature point set of the packaging box. In the feature extraction process, computer vision algorithms such as SIFT (Scale Invariant Feature Transform), SURF (Speeded Robust Features), and ORB (Rapid Oriented Binary Descriptors) are used to extract stable key points on the packaging box and calculate its feature descriptors. The feature point set of the real-time image data is matched and calculated with the feature data set extracted from the CAD model data, and the actual position and posture of the packaging box is determined by the feature point correspondence matrix. The nearest neighbor search or feature point filtering algorithm based on the RANSAC (Random Sampling Consistency) method is used to remove incorrect matching points and obtain a high-precision feature point correspondence matrix. This matrix describes the spatial mapping relationship between the feature points in the real-time image data and the predefined feature points in the CAD data. Based on the feature point correspondence matrix and the transformation matrix, a three-dimensional pose solution is performed to determine the position coordinate data of the packaging box. In this process, the PnP (Perspective-n-Point) algorithm is used to solve the transformation relationship between the camera coordinate system and the packaging box coordinate system to obtain the precise position of the packaging box in the visual coordinate system. At the same time, combined with the conversion matrix of the robot base coordinate system and the visual coordinate system, the position data of the packaging box is converted to the robot base coordinate system to ensure that the calculation of the UV inkjet trajectory is based on the correct spatial reference coordinates. According to the position coordinate data and the spatial calibration data, the spatial projection transformation is performed to obtain the posture angle data of the UV printing area. Through the known UV nozzle installation offset vector and the position data of the packaging box, the normal vector of the packaging box surface is solved, and the optimal inkjet angle of the UV nozzle is calculated to ensure that the ink can be evenly attached and achieve the best curing effect. The posture angle data of the UV printing area is obtained.

[0018] 104. Perform multi-segment trajectory planning on the inkjet trajectory according to the position coordinate data and the attitude angle data to obtain initial printing trajectory control data that meets the UV ink droplet jetting spacing requirement; Specifically, the UV printing area is grid discretized, and the continuous printing area is converted into regular dot matrix data. The adaptive grid division method is used to reasonably adjust the size of the grid unit according to the geometric characteristics of the packaging box, the diffusion characteristics of the UV ink droplets, and the printing accuracy requirements to ensure the uniform distribution of the printing dot matrix data. After the grid division is completed, the appropriate printing path is calculated based on the arrangement of the grid units, and the path is segmented to obtain the segmented trajectory sequence and the connection point data between each segment trajectory to ensure that the printing path can cover the entire UV printing area and reduce the printing defects caused by the discontinuous path. Combined with the trajectory connection point data and the posture angle data of the packaging box, motion interpolation calculation is performed to obtain the speed trajectory data and acceleration trajectory data required by the UV nozzle during the entire printing process. Since the movement of the UV nozzle needs to meet certain dynamic characteristics and ensure the stability of the speed during the inkjet process, the trajectory is smoothed by using the quintic B-spline interpolation or cubic spline interpolation method to optimize the speed and acceleration transition of the nozzle at each injection point, so that no mutation or vibration occurs during the printing process. Considering the curvature change of the packaging box surface, when printing on curved or irregular surfaces, the motion parameters of the nozzle are dynamically adjusted so that the ink droplets can accurately fall on the target area to avoid ink droplet deviation or printing blur due to changes in posture angles. The velocity trajectory data and acceleration trajectory data are dynamically constrained to ensure that the movement of the nozzle meets the mechanical properties of the actual equipment and the responsiveness of the injection system. The maximum acceleration, maximum speed and trigger timing constraints of the UV nozzle and the inkjet system are analyzed, and then the velocity and acceleration trajectories are constrained and adjusted through the optimization algorithm so that the motion trajectory meets the requirements of printing accuracy without exceeding the dynamic performance limit of the nozzle. The optimized trajectory data is used to calculate the timing data of inkjet, that is, to determine the injection time point of the nozzle on each printing path to ensure that the inkjet moment is synchronized with the nozzle motion trajectory. In order to optimize the inkjet quality, the segmented trajectory sequence is processed for spacing uniformity, that is, the position of the printing point is adjusted based on the inkjet timing data so that the spacing between the ink droplets remains uniform, thereby avoiding the stripe effect or overlapping printing caused by uneven injection intervals. The trajectory fitting calculation is performed according to the ink droplet ejection position sequence and the UV printing dot matrix data to obtain the initial printing trajectory control data that meets the printing requirements.

[0019] 105. Perform UV light source synchronization control calculation based on the initial printing trajectory control data to obtain UV light source power modulation parameters and UV light source trigger timing data.

[0020] Specifically, the initial printing trajectory control data is subjected to trajectory segment analysis and time series discretization processing, and the UV printing discrete point sequence and ink droplet deposition time data are calculated. The continuous printing trajectory is divided into a series of discrete printing points, and the specific time point of each ink droplet injection is determined by the time discretization method. This process is calculated in combination with the movement speed of the nozzle, the injection frequency and the physical properties of the UV ink to ensure that the distribution of the printing points is uniform, and the inkjet process can be strictly synchronized with the curing rhythm of the UV light source. The spatial distance matrix between adjacent ink droplets is calculated according to the UV printing discrete point sequence to determine the overlap rate data of the UV curing area. Since UV inkjet printing requires multiple injections to cover the entire printing area, the distance and arrangement between adjacent ink droplets directly affect the effect of UV curing. By calculating the distribution matrix of ink droplets in space, the ink droplet coverage in different areas is analyzed, and the light overlap problem that occurs during the UV curing process is judged accordingly. The Euclidean distance calculation method is used, combined with the printing grid data, to calculate the average spacing between adjacent ink droplets, and analyze the overlap degree of the UV curing area to ensure that the final printing quality will not be affected by excessive or insufficient UV energy during the curing process. The light source energy distribution is calculated based on the UV curing area overlap rate data to determine the spot coverage parameters and UV energy density data. The energy distribution of the UV light source is affected by the light source power, spot shape and beam divergence angle. When calculating the light source energy distribution, a UV illumination model is established to simulate the energy attenuation of the UV light source at different distances, and the UV energy acceptance of each ink droplet is calculated in combination with the arrangement of the printing points. The calculation of the spot coverage parameters needs to consider the irradiation angle of the light source and the diffusion characteristics of the light beam to ensure that the spot can cover all the ink drop areas that need to be cured and will not cause overexposure or underexposure. At the same time, the calculation of the UV energy density data is based on the deposition position of the ink droplets and the curing time requirements to ensure that the UV light energy can be evenly distributed throughout the printing area, so that the ink can be fully cured without incomplete curing due to insufficient energy, or overcuring or material damage due to excessive energy. The spot coverage parameters and the ink droplet deposition time data are synchronously optimized to generate the trigger timing data of the UV light source. The time synchronization control algorithm is used to optimize the on and off time of the light source to match the rhythm of inkjet, and the triggering time of the light source can be dynamically adjusted according to the UV energy demand of different areas. Power compensation calculation is performed based on UV energy density data and UV curing area overlap rate data to adjust the power output of the UV light source. The PID control algorithm or the adaptive power adjustment algorithm based on the neural network is used to dynamically adjust the output power of the UV light source so that it can output the most appropriate energy level in different curing areas, thereby ensuring the uniformity and stability of the UV curing process. The UV light source trigger timing data and the power modulation parameters of the UV light source are obtained.

[0021] The spot coverage parameters are spatially discretized to construct UV spot grid data and spot center coordinate data. The UV light source uses a collimating lens or a focusing optical system to form a spot. Its irradiation range is affected by the light source power, beam divergence angle, and the shape of the inkjet area. When calculating the spot grid data, the energy distribution of the spot is modeled, and the entire irradiation area is decomposed into multiple discrete grid units using a grid division method, so as to accurately characterize the irradiation intensity distribution of the UV light source at different positions. At the same time, the center point coordinate data of the spot is aligned with the printing area to ensure that the spatial distribution of the light source can cover all ink drop positions that need to be cured, thereby avoiding the problem of blind spots or energy waste. Based on the UV spot grid data and the ink drop deposition time data, a spatiotemporal registration calculation is performed to determine the correspondence matrix between the spot and the ink drop and the time delay parameter. Since the irradiation process of the UV light source is time-asynchronous with the inkjet process, the motion characteristics of the inkjet trajectory, the moving speed of the spot, and the optimal time window for curing need to be considered in the calculation. By establishing a spatiotemporal registration model, the relationship between the ink droplet deposition moment and the light source irradiation time is analyzed, so as to calculate the time delay parameter between each spot grid unit and the corresponding ink droplet, and adjust the trigger timing of the light source based on the parameter to ensure the best synchronization of UV curing. The light intensity distribution is calculated for the position correspondence matrix to obtain the irradiation intensity distribution diagram and energy accumulation curve data of the UV light source. The calculation of the light intensity distribution adopts the Gaussian spot model or the Lambertian radiation model to simulate the energy attenuation of the UV light source at different angles and distances, and the light intensity is numerically calculated in combination with the spot grid data. By constructing the UV irradiation intensity distribution diagram, the energy distribution of the light source in the entire printing area is analyzed, and the energy accumulation curve data is combined to determine whether the UV energy in different areas meets the curing requirements. If the UV energy in some areas is low, it will lead to incomplete curing, and too high energy will cause over-curing of the material. Therefore, the core goal of the light intensity distribution calculation is to ensure that the UV energy in all printing areas is evenly distributed and meets the requirements of the curing process. The trigger sequence is optimized according to the time delay parameter and the energy accumulation curve data to generate the trigger timing data of the UV light source. During the optimization process, the on and off time of the light source is adjusted based on the time delay parameter to ensure that the UV curing process does not affect the normal deposition and diffusion of the ink droplets. The acceleration and speed changes of the inkjet trajectory are comprehensively considered to ensure that the trigger frequency of the UV light source can adapt to the changes in different speed ranges during the printing process, thereby avoiding the problem of uneven curing caused by the mismatch between the light source trigger time and the ink droplet position. Energy compensation calculations are performed based on UV energy density data and UV curing area overlap rate data to optimize the power output of the UV light source. During the UV curing process, since there are overlapping areas in the spatial distribution of the light spots, the energy accumulation effect between adjacent light spots will affect the curing quality.In order to ensure the uniformity of UV energy, the energy contribution of each light spot is calculated, and the power distribution of the UV light source in different areas is adjusted through the energy compensation algorithm, so that the UV irradiation energy can be evenly distributed in the entire printing area. The calculation of the energy distribution weight needs to be combined with the spatial distribution of the ink droplets to ensure that each printing point can obtain sufficient UV energy, thereby avoiding the problem of incomplete curing due to insufficient local energy. The power compensation coefficient and energy distribution weight are numerically optimized, and nonlinear optimization methods such as gradient descent or genetic algorithm are used to minimize the unevenness of UV energy distribution and ensure that the power output of the UV light source meets the optimal setting of the printing process, and the UV light source power modulation parameters are obtained.

[0022] In the embodiment of the present invention, by performing feature extraction and edge detection on the CAD model data of the packaging box, the precise positioning and posture recognition of the packaging box position are realized in combination with machine vision technology, and the positioning deviation in the printing process is effectively avoided. A multi-segment trajectory planning method is adopted, and the uniformity of the ink drop spacing and the consistency of the curing effect are ensured through dynamic optimization of the inkjet trajectory and synchronous control of the UV light source. An accurate conversion relationship between the visual coordinate system and the robot base coordinate system is established, and the high-precision calibration of the UV nozzle position is realized, thereby improving the spatial positioning accuracy of the printing system. By calculating the overlap rate and energy density distribution of the UV curing area in real time, the power output and trigger timing of the UV light source are dynamically adjusted to achieve uniform curing of the ink droplets. Based on the synchronous optimization of the spot coverage range parameters and the ink drop deposition time data, the precise coordination of the UV light source and the inkjet system is achieved, and the stability of the printing quality is guaranteed. By real-time compensation of the UV light source power and optimization calculation of energy distribution, the problem of uneven curing of ink droplets at different positions is effectively solved, and the printing quality is improved.

[0023] In a specific embodiment, the process of executing step 101 may specifically include the following steps: Perform geometric edge extraction operation on the CAD model data of the packaging box to obtain edge contour data and edge line segment set of the packaging box; Calculate the intersection points and select the feature points of the edge segment set to obtain the corner point position data and corner point connection relationship data of the packaging box; Perform curvature analysis and surface smoothness calculation on edge profile data to obtain the reflection coefficient and material uniformity data of the packaging box surface; The printing resolution is optimized based on the corner point position data and material uniformity data to obtain the inkjet resolution parameters of the UV printing area, and the reflection coefficient is spatially mapped to obtain the reflection intensity distribution map and light intensity compensation coefficient of the UV printing area; A feature data set is constructed based on edge contour data, corner point position data, inkjet resolution parameters and reflection coefficient.

[0024] Specifically, the CAD model is parsed to obtain the geometric contour information of the packaging box. The CAD data of the packaging box is edge detected using a gradient operator method (such as Sobel, Prewitt, or Canny) to obtain the edge contour data of the packaging box. Assuming that the CAD model is stored in a vector format, its edge line segment set is directly extracted through geometric calculation. Assume Represents a set of edge segments, where each segment From the starting point coordinates and the end point coordinates Indicates that:

[0025] Calculate the intersection of the edge line segments to identify the corners of the box. and Endpoints , as well as , If , then the intersection point is obtained by solving the linear equations. The equation is:

[0026] The slope ,intercept . Similarly, the line segment The equation is:

[0027] The intersection point By solving the following system of equations:

[0028]

[0029] All the intersection points obtained constitute the corner point position data set , and calculate the connection relationship of the corner points, that is, determine which corner points are connected by edge segments, so as to build a complete topological structure of the packaging box. Perform curvature analysis on the edge contour data to calculate the geometric characteristics of the packaging box surface. The curvature calculation is completed by the curve differential geometry method. For the two-dimensional contour curve , curvature Defined as:

[0030] in, is the second-order derivative, is the first-order derivative. For three-dimensional surfaces, the principal curvature is calculated by the principal curvature calculation method. :

[0031] in is the mean curvature, is the Gaussian curvature. These curvature data are used to determine the surface flatness of the packaging box and to optimize the inkjet quality. While calculating the surface curvature, the surface smoothness is calculated to obtain the uniformity data of the packaging box material. The normal vector change rate is used to measure the smoothness of the surface. Suppose the surface normal vector is , then the smoothness is defined as:

[0032] in, is the surface area, is the gradient of the normal vector, The smaller the value, the smoother the surface, and vice versa. By calculating the surface smoothness, the inkjet resolution of the UV printing area is optimized to adapt it to different surface materials. The printing resolution is optimized based on the corner position data and material uniformity data to ensure that the accuracy of UV inkjet is consistent in different areas. Inkjet resolution parameters Defined as:

[0033] in, is the base resolution, is the surface smoothness, To optimize the weight factor. For smooth areas, the resolution is kept high, while for rough areas, the resolution is appropriately reduced to reduce the unevenness of ink droplet diffusion. The reflection coefficient is spatially mapped to obtain the reflection intensity distribution map of the UV printing area. Reflection coefficient Calculated by the lighting model, for example, using the Lambert reflection model:

[0034] in, is the surface reflectivity, is the incident angle, is the distance between the light source and the surface. According to the spatial distribution of the reflection coefficient, the light intensity compensation coefficient is calculated. :

[0035] in, is the target light intensity, The current measured light intensity is used to dynamically adjust the irradiation power of the UV light source to optimize the curing effect. A complete feature data set is constructed by integrating edge profile data, corner point position data, inkjet resolution parameters and reflection coefficient.

[0036] In a specific embodiment, the process of executing step 102 may specifically include the following steps: Perform feature point detection and extraction on the calibration plate image captured by the camera to obtain pixel coordinate data and sub-pixel coordinate data of the corner points of the calibration plate; Perform intrinsic calibration calculation on pixel coordinate data and sub-pixel coordinate data to obtain the camera's intrinsic parameter matrix and distortion coefficient matrix, and perform spatial pose optimization based on the intrinsic parameter matrix and distortion coefficient matrix to obtain the camera's extrinsic parameter matrix and projection transformation matrix; Based on the projection transformation matrix, the coordinates of the robot end reference point are transformed to obtain the conversion matrix between the visual coordinate system and the robot base coordinate system, and multi-point sampling measurement is performed on the position of the UV nozzle relative to the robot end to obtain the installation offset vector of the UV nozzle; The coordinate system compensation calculation is performed according to the conversion matrix and the installation offset vector to obtain the spatial calibration data of the UV nozzle installation position.

[0037] Specifically, a high-precision calibration plate is used for image acquisition, and a computer vision algorithm is used to extract the pixel coordinate data and sub-pixel coordinate data of the corner points of the calibration plate. The calibration plate adopts a checkerboard or dot array pattern with a regular geometric structure, and the Harris corner point detection function is used for feature point detection. Assume that the number of corner points on the calibration plate is , then the pixel coordinate data set is expressed as: ; in, Respectively represent The pixel coordinates of the corner points are obtained by using the sub-pixel precision method. By performing quadratic interpolation fitting in the local area, the accuracy of the corner point coordinates is improved to the decimal level, thereby obtaining more accurate sub-pixel coordinate data. The pixel coordinate data and sub-pixel coordinate data are calibrated with internal parameters to calculate the camera's intrinsic parameter matrix and distortion coefficient matrix. The camera's imaging model is represented by the perspective projection equation, that is, the three-dimensional world coordinate Transform to 2D pixel coordinates through camera projection The relationship is expressed as:

[0038] in, is the normalization factor, is the camera's intrinsic parameter matrix, including the focal length and the principal point coordinates :

[0039] The distortion coefficient matrix is ​​used to describe lens distortion, including radial distortion coefficients and tangential distortion coefficient :

[0040] These parameters are calibrated using nonlinear optimization methods (such as the Levenberg-Marquardt algorithm) to minimize the projection error, that is, to optimize the objective function:

[0041] in, is the real pixel coordinate, is the pixel coordinate after projection transformation. After completing the intrinsic parameter calibration, calculate the camera's extrinsic parameter matrix, that is, the rotation matrix and translation vector , which is used to describe the position relationship of the camera coordinate system relative to the world coordinate system. The external parameter matrix is ​​solved by solving the PnP (Perspective-n-Point) problem, that is, by at least 4 three-dimensional physical coordinate points The corresponding two-dimensional pixel coordinate point To find out :

[0042] The RANSAC algorithm is used to remove abnormal matching points, and the least squares optimization method is used to obtain the optimal solution, and finally the camera projection transformation matrix is ​​obtained:

[0043] Using this projection transformation matrix, the coordinates of the robot end reference point are transformed from the world coordinate system to the camera coordinate system and then to the robot base coordinate system. Assume that the position of the robot end reference point in the world coordinate system is , then its projection in the camera coordinate system is:

[0044] Through the coordinate transformation relationship matrix between the robot and the camera (Transformation matrix from visual coordinate system to robot base coordinate system), obtain the reference point position in the robot base coordinate system:

[0045] The spatial position of the UV nozzle is measured at multiple points to obtain its installation offset vector relative to the end of the robot. Assume that the actual injection point coordinates of the UV nozzle are , and the coordinates of the calibration point at the end of the robot are , then the installation offset vector of the UV nozzle It is expressed as:

[0046] In order to improve the measurement accuracy, the measurement is performed in multiple different robot postures, and the offset vector is optimized by the least squares method to reduce the measurement deviation caused by mechanical installation errors. And the installation offset vector of the UV nozzle Perform coordinate system compensation calculation to obtain the spatial calibration data of the UV nozzle. This compensation data is used to correct the robot printing trajectory to ensure the accuracy of the inkjet path. Assume that the expected injection position of the UV nozzle is , then the final injection coordinates after compensation are:

[0047] In a specific embodiment, the process of executing step 103 may specifically include the following steps: Perform multi-scale edge detection operations on the real-time image data of the packaging box to obtain the edge point set and edge intensity matrix of the packaging box, and perform adaptive threshold segmentation and morphological processing on the edge point set to obtain the refined edge contour and contour line segment data of the packaging box; Feature point extraction and descriptor calculation are performed based on the refined edge contour to obtain the feature point set of real-time image data, and matching calculation is performed based on the feature point set and the feature data set to obtain the feature point correspondence matrix; The three-dimensional pose is solved based on the feature point correspondence matrix and the transformation matrix to obtain the position coordinate data of the packaging box; The spatial projection transformation is performed according to the position coordinate data and the spatial calibration data to obtain the posture angle data of the UV printing area.

[0048] Specifically, the image of the packaging box is processed using a high-precision computer vision method. A multi-scale edge detection method is used to extract edge features at different scales to improve the robustness of detection. During the edge detection process, a Gaussian filter function is applied to smooth the image to reduce noise interference:

[0049] in, is the Gaussian kernel function, is a smoothing parameter that controls the scale of filtering. Then the Canny edge detection algorithm is used to detect the edge of the packaging box. The core of this algorithm is to calculate the gradient of the image and use non-maximum suppression and double threshold processing to enhance the edge contrast. Suppose the original image is , then its gradient amplitude and the gradient direction The calculation is as follows:

[0050]

[0051] in, and The images are and After edge detection, we get the edge point set of the packaging box. and the edge strength matrix , which represents the edge strength of different pixels in the image. In order to optimize the edge detection results, the edge point set is segmented by adaptive threshold, that is, the threshold of edge detection is dynamically adjusted according to the gradient change of local pixels. :

[0052] in, is the scale factor, . Use morphological processing methods (such as expansion, corrosion, opening and closing operations) to optimize edge data to eliminate isolated points and broken edges and obtain refined edge contours. and the contour segment set . Feature point extraction and descriptor calculation are performed based on the refined edge contour to match the feature points of the packaging box in the image with the feature point set of the CAD reference data. In the feature point extraction process, SIFT (Scale Invariant Feature Transform) or ORB (Rapid Binary Descriptor) algorithm is used to extract a stable feature point set on the surface of the packaging box. The core of SIFT feature point extraction is to construct a Gaussian scale space and find extreme points at different scales. Assume that the input image is , then its scale space is expressed as:

[0053] in, is the Gaussian kernel, Represents the convolution operation. The extreme points in the scale space are calculated by the DOG (Difference of Gaussian) operator:

[0054] After finding the extreme point, calculate the key point descriptor to generate the feature point set ,in It is a 128-dimensional SIFT descriptor. These feature points are matched with the feature data set of the CAD model, and the feature point correspondence matrix is ​​solved using the nearest neighbor search (KNN) or FLANN matching algorithm. :

[0055] in, and Represents the matching pairs of feature points in the image and CAD reference feature points respectively. Based on the feature point correspondence matrix and the transformation matrix , perform three-dimensional pose calculation to obtain the position coordinate data of the packaging box. Feature point matching forms a set of spatial point pairs, and the PnP (Perspective-n-Point) method is used to calculate the rotation matrix of the packaging box relative to the camera. and translation vector ,Right now:

[0056] in, is the position of the CAD reference feature point in the world coordinate system, is the pixel coordinate in the image, is the camera intrinsic parameter matrix. Solving for and Finally, calculate the position of the box in the robot coordinate system:

[0057] in, is the transformation matrix from the visual coordinate system to the robot base coordinate system. and spatial calibration data , perform spatial projection transformation to obtain the attitude angle data of the UV printing area. Assume that the UV nozzle installation offset is , then the final pose of the UV printing area is:

[0058] The attitude angle data is obtained by the rotation matrix Convert to Euler angles To facilitate robot control:

[0059] In this embodiment, the edge point set is adaptively thresholded and morphologically processed to obtain refined edge contour and contour line segment data of the packaging box, including: estimating the Laplace distribution parameters of the edge point set to obtain position parameters and scale parameters; constructing a probability density function based on the position parameters and scale parameters to obtain a distribution model and noise characteristic parameters of the edge points; performing Gaussian scale mixture decomposition on the distribution model to obtain a mixture weight coefficient and a scale factor matrix; performing variational Bayesian inference based on the mixture weight coefficient and the scale factor matrix to obtain a posterior probability distribution and model parameter estimates; performing reliability assessment on the edge points based on the posterior probability distribution to obtain confidence data and outlier markers of the edge points; performing threshold adaptive calculation based on the confidence data and noise characteristic parameters to obtain a dynamic segmentation threshold and regional growth parameters; performing morphological filtering on the outlier markers to obtain edge connectivity indicators and regional consistency data; performing edge extraction operations based on the dynamic segmentation threshold and regional growth parameters to obtain refined edge contour and contour line segment data of the packaging box.

[0060] Among them, three-dimensional posture solution is performed based on the feature point correspondence matrix and the transformation matrix to obtain the position coordinate data of the packaging box, including: performing feature vector decomposition operation on the feature point correspondence matrix to obtain the feature point spatial distribution weight and the main direction vector; screening and grouping the feature points according to the feature point spatial distribution weight to obtain the effective feature point set and feature point clustering data; performing homography matrix calculation based on the effective feature point set and the transformation matrix to obtain the projection transformation matrix from the two-dimensional image plane to the three-dimensional space; performing RANSAC algorithm optimization on the effective feature point set to obtain geometric consistency constraint parameters and external point removal results; performing PnP solution operation based on the projection transformation matrix and the geometric consistency constraint parameters to obtain the rotation matrix and translation vector of the packaging box; performing quaternion decomposition calculation on the rotation matrix to obtain the posture angle parameters and rotation axis vector of the packaging box; performing coordinate transformation calculation based on the translation vector and the main direction vector to obtain the position coordinates of the packaging box in the robot base coordinate system; performing coordinate system alignment operation based on the posture angle parameters and the position coordinates to obtain the position coordinate data of the packaging box.

[0061] Specifically, a spatial projection transformation is performed according to the position coordinate data and the spatial calibration data to obtain the posture angle data of the UV printing area, including: performing a coordinate system conversion calculation on the position coordinate data to obtain the relative position matrix and posture matrix of the packaging box in the UV nozzle coordinate system; performing deviation compensation on the relative position matrix based on the spatial calibration data to obtain the spatial position vector of the UV nozzle relative to the surface of the packaging box; performing Euler angle decomposition operation on the posture matrix to obtain the inclination angle data and normal vector data of the packaging box surface; performing vertical distance calculation according to the normal vector data and the spatial position vector to obtain the height parameter and angle deviation data from the UV nozzle to the printing surface; performing boundary extraction of the UV printing area based on the inclination angle data to obtain the contour point set and the coordinates of the center of the printing area; performing principal component analysis operation on the contour point set to obtain the major axis direction vector and the minor axis direction vector of the printing area; performing posture compensation calculation according to the major axis direction vector and the angle deviation data to obtain the correction angle data of the UV printing area; performing spatial relationship matrix calculation based on the correction angle data and the height parameter to obtain the posture angle data of the UV printing area.

[0062] In a specific embodiment, the process of executing step 104 may specifically include the following steps: The UV printing area is subjected to grid discretization processing to obtain UV printing dot matrix data and grid unit division data, and the printing path segmentation calculation is performed based on the grid unit division data to obtain the segmented trajectory sequence and trajectory connection point data; Perform motion interpolation calculation based on the trajectory connection point data and posture angle data to obtain the velocity trajectory data and acceleration trajectory data of the UV nozzle; The velocity trajectory data and the acceleration trajectory data are optimized with dynamic constraints to obtain the ejection timing data of the UV nozzle, and the segmented trajectory sequence is processed with spacing uniformity based on the ejection timing data to obtain the ink drop ejection position sequence; The trajectory fitting calculation is performed according to the ink droplet ejection position sequence and the UV printing dot matrix data to obtain the initial printing trajectory control data.

[0063] Specifically, the UV printing area is spatially divided so that the entire printing area can be evenly covered while ensuring the rationality and continuity of the inkjet trajectory. In this process, the grid discretization method is used to divide the printing area into regular unit grids. The size of each grid unit is determined by the jet resolution of the nozzle and the ink droplet diffusion characteristics. Assume that the total width and height of the printing area are and , then the grid unit is divided by the grid spacing Calculate the number of grids :

[0064] in, Determined by the minimum jetting resolution of the UV nozzle, that is, it must be ensured that the ink droplets in adjacent grid cells do not overlap or have gaps. For each grid cell, define the coordinates of its center point , forming a printing dot matrix data set:

[0065] The printing path is calculated based on the grid unit division data and the trajectory is segmented. The path planning methods include line scanning, serpentine path, and contour following. For UV printing in regular rectangular areas, the serpentine path is used to optimize the printing efficiency, so that the UV nozzle reduces the number of emergency stops when changing lines, thereby improving the stability of the printing. Assume that the number of segments of the printing path is , then the segmented trajectory sequence ( ) is calculated as:

[0066] At the same time, between every two segmented tracks, define the track connection point data , to ensure the continuity of the UV nozzle when switching track segments, that is:

[0067] After obtaining the segmented trajectory data, combine the trajectory connection point data and attitude angle data Perform motion interpolation calculation to obtain the velocity trajectory data and acceleration trajectory data of the UV nozzle. Assume that the motion time of the UV nozzle on a certain trajectory segment is , its location Expressed as a cubic spline interpolation function:

[0068] Speed ​​track and acceleration trajectory By taking the derivative of the position function we get:

[0069]

[0070] In order to ensure that the inkjet quality is not affected by the nozzle being too fast or too slow during movement, the velocity trajectory and acceleration trajectory are dynamically constrained and optimized. Assume that the maximum allowable acceleration of the UV nozzle is The maximum permissible speed is , then the optimization constraints are:

[0071] The quadratic programming optimization method is used to adjust the The value of is set to ensure that the printing trajectory is smooth and conforms to the motion characteristics of the UV nozzle. After completing the dynamic optimization, calculate the ejection timing data of the UV nozzle. The ejection timing is closely related to the motion state of the nozzle. Suppose the ink droplet ejection interval is , then the injection time point Calculated from the position and speed of the UV nozzle:

[0072] in, is the spatial distance between adjacent printing points, For the nozzle In order to ensure uniform distribution of ink droplets, after the injection timing is calculated, the segmented trajectory is processed to make the position sequence of the injection point uniform. With equal spacing:

[0073] in, Represents the Euclidean distance between adjacent ink droplets. Based on the optimized ink droplet ejection position sequence and UV printing dot matrix data, trajectory fitting calculation is performed to generate initial printing trajectory control data that meets the UV printing requirements. The goal of trajectory fitting is to ensure the smoothness of the inkjet path while ensuring that the ink droplets can accurately cover the entire UV printing area. The spline curve fitting method is used to make the printing trajectory smoother. Assuming the fitting trajectory Represented by a Bezier curve, then:

[0074] in, is the Bernstein polynomial:

[0075] Control points of a Bezier curve It is determined by the ink droplet ejection point after homogenization to ensure that the printing trajectory meets the actual process requirements.

[0076] Among them, the velocity trajectory data and the acceleration trajectory data are dynamically optimized to obtain the injection timing data of the UV nozzle, and the segmented trajectory sequence is evenly spaced based on the injection timing data to obtain the ink droplet injection position sequence, including: performing maximum speed limit analysis on the velocity trajectory data to obtain the velocity constraint threshold and the acceleration smoothing coefficient; performing dynamic characteristic calculation based on the acceleration trajectory data to obtain the jerk curve and mechanical vibration frequency data of the UV nozzle; performing motion stability analysis based on the jerk curve and the mechanical vibration frequency data to obtain the nozzle jitter amplitude and stability evaluation parameters; performing frequency domain filtering on the nozzle jitter amplitude to obtain the stable motion range and speed switching point data of the UV nozzle; performing time series planning based on the speed constraint threshold and the stable motion range to obtain the injection timing data of the UV nozzle; performing equal time interval sampling on the segmented trajectory sequence according to the injection timing data to obtain the initial injection point sequence; performing spatial position compensation based on the initial injection point sequence and the velocity switching point data to obtain the compensated injection position data; performing equal spacing optimization calculation on the compensated injection position data to obtain the ink droplet injection position sequence.

[0077] In a specific embodiment, the process of executing step 105 may specifically include the following steps: The initial printing trajectory control data is subjected to trajectory segment analysis and time series discretization processing to obtain the UV printing discrete point sequence and ink drop deposition time data; The spatial distance matrix between adjacent ink droplets is calculated based on the UV printing discrete point sequence to obtain the UV curing area overlap rate data; Calculate the light source energy distribution based on the UV curing area overlap rate data to obtain the spot coverage parameters and UV energy density data; The spot coverage parameters and ink droplet deposition time data are synchronously optimized to obtain the UV light source trigger timing data, and the power compensation calculation is performed based on the UV energy density data and the UV curing area overlap rate data to obtain the UV light source power modulation parameters.

[0078] Specifically, the initial printing trajectory control data is analyzed by trajectory segment, and the UV printing discrete point sequence and the deposition time data of each ink droplet are obtained through time series discretization processing. In this process, the printing trajectory is composed of a series of spatial points. The printing path is assumed to be a three-dimensional curve. ,in is a time variable. In order to discretize the trajectory, according to the printing resolution Perform equal-interval sampling to obtain a discrete point sequence:

[0079] in, is the total number of printed dots, Represents ink drop The printing timing data is determined by the spray frequency of the UV nozzle. And the actual movement speed of the nozzle Together, the deposition time of each ink droplet is expressed as:

[0080] After obtaining the sequence of printed discrete dots, the spatial distance matrix between adjacent ink droplets is calculated to analyze the overlap of the UV curing area. and The Euclidean distance between :

[0081] According to the spray diameter of UV nozzle And the diffusion radius of UV ink , calculate the overlap rate of adjacent ink droplets :

[0082] when When , it means that the adjacent ink droplets completely overlap, and when When there is a gap between adjacent ink droplets, adjust the printing spacing. To ensure reasonable curing quality. Based on the overlap rate data of the UV curing area, the energy distribution of the UV light source is calculated to ensure that each ink droplet receives the appropriate amount of UV energy so that it is fully cured without overexposure. The energy density of the UV light source is affected by the spot size, light source power, and illumination time. Assume that the power of the UV light source is , the distance from the light source to the printing surface is , the radius of the spot is , then the UV energy density at the center of the spot It is expressed as:

[0083] in, is the attenuation parameter of UV light in air. The coverage of UV spot is determined by the light intensity threshold. It is determined that the energy distribution at the edge of the light spot satisfies the Gaussian function:

[0084] in, is the light spot diffusion parameter. By integrating the light intensity, the effective coverage of the light spot is calculated. :

[0085] Calculate UV energy density data based on spot coverage and ink droplet deposition position :

[0086] in, To cover All the light spot centers. If Below the curing threshold , then you need to increase the lighting time, otherwise, if If the UV light source is too high, the light source power needs to be reduced. After calculating the UV energy density distribution, the spot coverage parameters and ink drop deposition time data are optimized synchronously to ensure that the trigger time of the UV light source matches the inkjet process. Assume that the trigger time of the UV light source is , the printing timing data is , then the goal of trigger timing optimization is to minimize the time error:

[0087] During the optimization process, the PID control algorithm is used to dynamically adjust the triggering time of the UV light source to match the inkjet path. Suppose the UV light source triggering time adjustment amount is ,but:

[0088] in, It is a PID control parameter. Based on the UV energy density data and the UV curing area overlap rate data, power compensation calculation is performed to ensure that the energy distribution of the UV light source in different areas is uniform. Power compensation coefficient The current energy density With target energy density The calculation results are:

[0089] if , indicating that the UV energy in the current area is insufficient, increase the light source power or increase the exposure time; if , indicating that the energy is too high, and the light source power needs to be reduced. Based on all calculation results, optimize the power modulation parameters of the UV light source :

[0090] Among them, the spatial distance matrix between adjacent ink droplets is calculated according to the UV printing discrete point sequence to obtain the UV curing area overlap rate data, including: performing spatial coordinate transformation on the UV printing discrete point sequence to obtain the three-dimensional position data and point set topological structure of the ink drop center point; constructing a K nearest neighbor search tree based on the three-dimensional position data to obtain the index relationship matrix and distance calculation parameters of adjacent ink droplets; performing connectivity analysis on the index relationship matrix to obtain the adjacency matrix and path connection data of the ink drop connection graph; performing overlapping area calculation according to the distance calculation parameters and the ink drop diffusion radius to obtain the intersection area data between the ink droplets; performing regional segmentation operation based on the intersection area data to obtain the boundary contour and area statistical data of the UV curing area; performing morphological processing on the boundary contour to obtain the geometric feature parameters and coverage index of the overlapping area; performing normalization calculation according to the coverage index and area statistical data to obtain the numerical distribution of the regional overlap rate; performing spatial interpolation operation based on the numerical distribution and path connection data to obtain the UV curing area overlap rate data.

[0091] In this embodiment, the energy distribution of the light source is calculated based on the UV curing area overlap rate data to obtain the spot coverage range parameters and UV energy density data, including: spatial grid division of the UV curing area overlap rate data to obtain the grid unit data and node position matrix of the overlapping area; light intensity distribution model is established based on the grid unit data to obtain the Gaussian distribution parameters and energy attenuation coefficient of the UV light source; the projection angle of the UV light source to the curing surface is calculated according to the node position matrix to obtain the spot projection transformation matrix and the effective irradiation range; energy density mapping is performed on the spot projection transformation matrix to obtain the energy distribution function and irradiation intensity diagram of the UV light source; superposition calculation is performed based on the energy distribution function and the overlap rate data to obtain the cumulative energy distribution matrix and energy gradient data; spot boundary extraction is performed based on the energy gradient data to obtain the spot coverage range parameters and the edge transition zone width; energy uniformity analysis is performed on the cumulative energy distribution matrix to obtain the energy density change curve and the fluctuation coefficient; energy compensation calculation is performed based on the fluctuation coefficient and the edge transition zone width to obtain the UV energy density data.

[0092] In a specific embodiment, the execution step performs synchronous optimization calculation on the spot coverage range parameter and the ink droplet deposition time data to obtain the UV light source trigger timing data, and performs power compensation calculation based on the UV energy density data and the UV curing area overlap rate data to obtain the UV light source power modulation parameter. The process can specifically include the following steps: The spot coverage parameters are spatially discretized to obtain UV spot grid data and spot center point coordinate data; Based on the UV spot grid data and ink droplet deposition time data, the spatiotemporal registration calculation is performed to obtain the position correspondence matrix and time delay parameters of the spot and ink droplet; Calculate the light intensity distribution of the position correspondence matrix to obtain the UV light source irradiation intensity distribution diagram and energy accumulation curve data; The trigger sequence is optimized according to the time delay parameters and the energy accumulation curve data to obtain the UV light source triggering timing data; Energy compensation calculation is performed based on UV energy density data and UV curing area overlap rate data to obtain the power compensation coefficient and energy allocation weight of the UV light source; The power compensation coefficient and energy allocation weight are numerically optimized to obtain the power modulation parameters of the UV light source.

[0093] Specifically, a spatial distribution model of UV light spots is constructed to grid the UV irradiation area. Assume that the projection area of ​​the UV light source is The average radius of the spot is , the entire UV illumination area is divided into a series of grid cells, and the size of each grid cell depends on the spot spacing ,Right now:

[0094] in, Represents the number of grids in the horizontal and vertical directions respectively. For each light spot, the coordinates of its center point are expressed as:

[0095] in, is the grid index of the light spot. Through grid discretization processing, the UV light spot grid data is obtained And the coordinate data of the center point of the spot , thus establishing a mathematical model of the UV illumination area. Based on the UV spot grid data and the ink droplet deposition time data, a spatiotemporal registration calculation is performed to ensure that the irradiation time and position of the UV light source can strictly match the ink droplet deposition process. Assume that the ink droplet deposition point set is , where the spatial coordinates of each ink droplet are:

[0096] in, represents the spatial position of the ink drop, In order to establish the spatial mapping relationship between the UV light spot and the ink droplet, the Euclidean distance matrix between the light spot and the ink droplet is calculated. :

[0097] in, Indicates the center point of the light spot With ink drop deposition point If , then the light spot Covered with ink drops , forming the corresponding relationship matrix between light spots and ink droplets:

[0098] At the same time, due to the time delay between the irradiation of the UV light source and the deposition of the ink droplets, the time delay parameter is calculated. :

[0099] in, UV spot The triggering moment. If Too large, resulting in the ink droplets not being cured at the best time, so adjust the trigger time of the UV light source to minimize the time error:

[0100] After completing the time-space registration calculation, the light intensity distribution of the UV light source is calculated based on the light spot position correspondence matrix to obtain the UV irradiation intensity distribution diagram and energy accumulation curve data. The energy attenuation of the UV light source usually follows a Gaussian distribution. Assume that the light intensity at the center of the light spot is , then the light intensity at a point It is expressed as:

[0101] in, is the spot diffusion parameter. For each grid cell, calculate the total UV energy density it receives:

[0102] The energy accumulation curve data of the UV light source is calculated by integration to ensure that the energy is evenly distributed in the entire printing area. If the energy accumulation curve of a certain area is too high or too low, the trigger sequence of the UV light source is adjusted. The trigger sequence is optimized according to the time delay parameter and the energy accumulation curve data to ensure that the trigger time of the UV light source can match the inkjet process to the greatest extent. Assume that the trigger time of the UV light source is , the inkjet timing data is , then the optimization goal is to minimize the time error:

[0103] During the optimization process, the PID control algorithm is used to dynamically adjust the triggering time of the UV light source to match the inkjet path. Suppose the UV light source triggering time adjustment amount is ,but:

[0104] in, It is a PID control parameter. Based on the UV energy density data and the UV curing area overlap rate data, energy compensation calculation is performed to ensure that the energy distribution of the UV light source in different areas is uniform. Power compensation coefficient The current energy density With target energy density The calculation results are:

[0105] if , indicating that the UV energy in the current area is insufficient, increase the light source power or increase the exposure time; if , indicating that the energy is too high, then reduce the light source power. Based on all calculation results, optimize the power modulation parameters of the UV light source :

[0106] The above describes the UV printing method for packaging boxes in the embodiment of the present invention. The following describes the UV printing device for packaging boxes in the embodiment of the present invention. Figure 2 In one embodiment of the present invention, a packaging box UV printing device includes: The feature extraction module 201 is used to extract features from the CAD model data of the packaging box to obtain a feature data set of the packaging box; The coordinate mapping module 202 is used to coordinate map the robot workspace to obtain the conversion matrix between the visual coordinate system and the robot base coordinate system and the spatial calibration data of the UV nozzle installation position; The feature point matching module 203 is used to perform edge detection and feature point matching on the packaging box based on the conversion matrix and the spatial calibration data, and obtain the position coordinate data of the packaging box and the posture angle data of the UV printing area; The trajectory planning module 204 is used to perform multi-segment trajectory planning on the inkjet trajectory according to the position coordinate data and the attitude angle data, and obtain the initial printing trajectory control data that meets the UV ink droplet jetting spacing requirements; The synchronous control module 205 is used to perform UV light source synchronous control calculation based on the initial printing trajectory control data to obtain UV light source power modulation parameters and UV light source triggering timing data.

[0107] Through the collaboration of the above components, the precise positioning and posture recognition of the packaging box position are achieved by extracting features and detecting edges of the packaging box CAD model data, combined with machine vision technology, effectively avoiding positioning deviations during the printing process. The multi-segment trajectory planning method is adopted, and the uniformity of the ink drop spacing and the consistency of the curing effect are ensured through dynamic optimization of the inkjet trajectory and synchronous control of the UV light source. The precise conversion relationship between the visual coordinate system and the robot base coordinate system is established, and the high-precision calibration of the UV nozzle position is achieved, which improves the spatial positioning accuracy of the printing system. By calculating the overlap rate and energy density distribution of the UV curing area in real time, the power output and trigger timing of the UV light source are dynamically adjusted to achieve uniform curing of the ink droplets. Based on the synchronous optimization of the spot coverage range parameters and the ink drop deposition time data, the precise coordination of the UV light source and the inkjet system is achieved, ensuring the stability of the printing quality. Through the real-time compensation of the UV light source power and the optimization calculation of the energy distribution, the problem of uneven curing of ink droplets at different positions is effectively solved, and the printing quality is improved.

[0108] above Figure 2 The middle packaging box UV printing device in the embodiment of the present invention is described in detail from the perspective of modular functional entity, and the packaging box UV printing device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0109] Figure 3 3 is a schematic diagram of the structure of a packaging box UV printing device provided by an embodiment of the present invention. The packaging box UV printing device 300 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 310 (for example, one or more processors) and a memory 320, and one or more storage media 330 (for example, one or more mass storage device terminals) storing application programs 333 or data 332. Among them, the memory 320 and the storage medium 330 can be short-term storage or permanent storage. The program stored in the storage medium 330 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the packaging box UV printing device 300. Furthermore, the processor 310 can be configured to communicate with the storage medium 330, and execute a series of instruction operations in the storage medium 330 on the packaging box UV printing device 300 to implement the steps of the above-mentioned packaging box UV printing method.

[0110] The packaging box UV printing device 300 may also include one or more power supplies 340, one or more wired or wireless network interfaces 350, one or more input and output interfaces 360, and / or one or more operating systems 331, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. It will be appreciated by those skilled in the art that Figure 3 The illustrated packaging box UV printing device structure does not constitute a limitation on the packaging box UV printing device provided by the present invention, and may include more or fewer components than illustrated, or a combination of certain components, or a different arrangement of components.

[0111] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0112] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the whole or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0113] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A packaging box UV printing method, characterized in that: The method comprises: Perform feature extraction on the CAD model data of the packaging box to obtain a feature data set of the packaging box; Carry out coordinate mapping of the robot workspace to obtain the conversion matrix between the visual coordinate system and the robot base coordinate system and the spatial calibration data of the UV nozzle installation position; Based on the conversion matrix and the spatial calibration data, edge detection and feature point matching are performed on the packaging box to obtain position coordinate data of the packaging box and posture angle data of the UV printing area; According to the position coordinate data and the attitude angle data, a multi-segment trajectory planning is performed on the inkjet trajectory to obtain initial printing trajectory control data that meets the UV ink droplet jetting spacing requirement; Based on the initial printing trajectory control data, a UV light source synchronous control calculation is performed to obtain UV light source power modulation parameters and UV light source triggering timing data.

2. The packaging box UV printing method according to claim 1, characterized in that: The step of extracting features from the CAD model data of the packaging box to obtain a feature data set of the packaging box includes: Performing geometric edge extraction operation on the CAD model data of the packaging box to obtain edge contour data and edge line segment set of the packaging box; Calculating intersection points and screening feature points on the edge line segment set to obtain corner point position data and corner point connection relationship data of the packaging box; Performing curvature analysis and surface smoothness calculation on the edge profile data to obtain reflection coefficient and material uniformity data of the packaging box surface; The printing resolution is optimized based on the corner point position data and the material uniformity data to obtain the inkjet resolution parameter of the UV printing area, and the reflection coefficient is spatially distributed mapped to obtain the reflection intensity distribution diagram and the light intensity compensation coefficient of the UV printing area; A feature data set is constructed according to the edge contour data, the corner point position data, the inkjet resolution parameter and the reflection coefficient.

3. The packaging box UV printing method according to claim 1, characterized in that: The coordinate mapping of the robot workspace is performed to obtain the conversion matrix between the visual coordinate system and the robot base coordinate system and the spatial calibration data of the UV nozzle installation position, including: Perform feature point detection and extraction on the calibration plate image captured by the camera to obtain pixel coordinate data and sub-pixel coordinate data of the corner points of the calibration plate; Performing an internal calibration calculation on the pixel coordinate data and the sub-pixel coordinate data to obtain an intrinsic parameter matrix and a distortion coefficient matrix of the camera, and performing spatial posture optimization based on the intrinsic parameter matrix and the distortion coefficient matrix to obtain an extrinsic parameter matrix and a projection transformation matrix of the camera; Based on the projection transformation matrix, the coordinates of the reference point at the end of the robot are transformed to obtain the conversion matrix between the visual coordinate system and the robot base coordinate system, and multi-point sampling measurement is performed on the position of the UV nozzle relative to the end of the robot to obtain the installation offset vector of the UV nozzle; A coordinate system compensation calculation is performed according to the conversion matrix and the installation offset vector to obtain spatial calibration data of the UV nozzle installation position.

4. The packaging box UV printing method according to claim 1, characterized in that: The method of performing edge detection and feature point matching on the packaging box based on the conversion matrix and the spatial calibration data to obtain position coordinate data of the packaging box and posture angle data of the UV printing area includes: Performing multi-scale edge detection operations on the real-time image data of the packaging box to obtain an edge point set and an edge intensity matrix of the packaging box, and performing adaptive threshold segmentation and morphological processing on the edge point set to obtain refined edge contour and contour line segment data of the packaging box; Extracting feature points and calculating descriptors based on the refined edge contour to obtain a feature point set of the real-time image data, and performing matching calculation based on the feature point set and the feature data set to obtain a feature point correspondence matrix; Perform three-dimensional pose calculation based on the feature point correspondence matrix and the transformation matrix to obtain position coordinate data of the packaging box; A spatial projection transformation is performed according to the position coordinate data and the spatial calibration data to obtain the posture angle data of the UV printing area.

5. The packaging box UV printing method according to claim 1, characterized in that: The method of performing multi-segment trajectory planning on the inkjet trajectory according to the position coordinate data and the attitude angle data to obtain initial printing trajectory control data that meets the UV ink droplet jetting spacing requirement includes: The UV printing area is subjected to grid discretization processing to obtain UV printing dot matrix data and grid unit division data, and a printing path segmentation calculation is performed based on the grid unit division data to obtain a segmented trajectory sequence and trajectory connection point data; Perform motion interpolation calculation according to the trajectory connection point data and the posture angle data to obtain the velocity trajectory data and acceleration trajectory data of the UV nozzle; Performing dynamic constraint optimization on the velocity trajectory data and the acceleration trajectory data to obtain the ejection timing data of the UV nozzle, and performing spacing uniformization processing on the segmented trajectory sequence based on the ejection timing data to obtain the ink drop ejection position sequence; A trajectory fitting calculation is performed according to the ink droplet ejection position sequence and the UV printing dot matrix data to obtain initial printing trajectory control data.

6. The packaging box UV printing method according to claim 1, characterized in that: The UV light source synchronization control calculation is performed based on the initial printing trajectory control data to obtain the UV light source power modulation parameters and UV light source trigger timing data, including: Performing trajectory segment analysis and time series discretization processing on the initial printing trajectory control data to obtain UV printing discrete point sequence and ink drop deposition time data; Calculate the spatial distance matrix between adjacent ink droplets according to the UV printing discrete point sequence to obtain UV curing area overlap rate data; Calculate the light source energy distribution based on the UV curing area overlap rate data to obtain the light spot coverage range parameters and UV energy density data; The spot coverage range parameter and the ink droplet deposition time data are synchronously optimized to obtain UV light source trigger timing data, and power compensation calculation is performed based on the UV energy density data and the UV curing area overlap rate data to obtain UV light source power modulation parameters.

7. The packaging box UV printing method according to claim 6, characterized in that: The synchronous optimization operation of the spot coverage range parameter and the ink droplet deposition time data is performed to obtain the UV light source trigger timing data, and the power compensation calculation is performed based on the UV energy density data and the UV curing area overlap rate data to obtain the UV light source power modulation parameter, including: Performing spatial discretization processing on the light spot coverage range parameters to obtain UV light spot grid data and light spot center point coordinate data; Performing spatiotemporal registration calculation based on the UV light spot grid data and the ink droplet deposition time data to obtain a position correspondence matrix between the light spot and the ink droplet and a time delay parameter; Calculating the light intensity distribution of the position correspondence matrix to obtain a UV light source irradiation intensity distribution diagram and energy accumulation curve data; Optimize the trigger sequence according to the time delay parameter and the energy accumulation curve data to obtain UV light source trigger timing data; Performing energy compensation calculation based on the UV energy density data and the UV curing area overlap rate data to obtain a power compensation coefficient and an energy allocation weight of the UV light source; The power compensation coefficient and the energy allocation weight are numerically optimized to obtain UV light source power modulation parameters.

8. A packaging box UV printing device, characterized in that: Used to perform the packaging box UV printing method according to any one of claims 1 to 7, the device comprises: A feature extraction module is used to extract features from the CAD model data of the packaging box to obtain a feature data set of the packaging box; The coordinate mapping module is used to coordinate map the robot workspace, obtain the conversion matrix between the visual coordinate system and the robot base coordinate system, and the spatial calibration data of the UV nozzle installation position; A feature point matching module, used to perform edge detection and feature point matching on the packaging box based on the conversion matrix and the spatial calibration data, to obtain position coordinate data of the packaging box and posture angle data of the UV printing area; A trajectory planning module, used to perform multi-segment trajectory planning on the inkjet trajectory according to the position coordinate data and the attitude angle data, and obtain initial printing trajectory control data that meets the UV ink droplet jetting spacing requirement; The synchronous control module is used to perform UV light source synchronous control calculation based on the initial printing trajectory control data to obtain UV light source power modulation parameters and UV light source triggering timing data.

9. A packaging box UV printing device, characterized in that: The packaging box UV printing device comprises: a memory and at least one processor, wherein instructions are stored in the memory; The at least one processor calls the instructions in the memory to enable the packaging box UV printing device to execute the packaging box UV printing method according to any one of claims 1-7.

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